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Optimal allocation of intermittent distributed generators in active distribution network
Author(s) -
Li Ke,
Zhang Shenxi,
Tai Nengling,
Chen Xi
Publication year - 2018
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.22581
Subject(s) - mathematical optimization , distributed generation , transformer , computer science , ac power , optimal allocation , genetic algorithm , photovoltaic system , interior point method , wind power , tap changer , dual (grammatical number) , engineering , renewable energy , electrical engineering , mathematics , voltage , art , literature
Nowadays, intermittent distributed generators (IDGs), represented by distributed wind turbine generators and photovoltaic generators, are developing rapidly. A multi‐scenario mathematical model with the objective of minimizing the annual carbon emission is proposed for the optimal allocation of IDGs in the active distribution network (ADN). The model takes into account three active measures, i.e. regulating the on‐load tap changer of the transformer, curtailing the active power of IDGs, and regulating the power factor of IDGs. K ‐means clustering method is introduced to reduce the number of scenarios and obtain the probability of each scenario. A hybrid solving strategy combining the adaptive genetic algorithm and primal‐dual interior point method is developed to solve the model. Case studies are carried out on the IEEE 33‐bus ADN. The optimal allocation schemes under different cases are compared, and the potential contribution of carbon emission reduction from active measures is studied. © 2018 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.